1. Field of the Invention
This invention relates generally to image processors of the type which are located on the focal plane of an imaging array, and more particularly to an improved image processor for removing non-uniformities which can distort the image processor's computations.
2. Description of the Related Art
The class of image sensors known as focal plane processors are integrated sensor circuits which combine some form of signal processing and an imaging array on a single die. The imaging array captures an image which strikes an array of pixel sensors lying on a focal plane. The focal plane is a light sensitive circuit on which the optical array focuses ambient light. The pixel sensors convert light into electrical signals. Generally, the focal plane is defined by the surface of a semiconductor device which has a plurality of light sensitive elements (photo-transconduction elements) formed thereon to achieve a pixel sensing capability.
The signal processing of a focal plane processor is often done in the analog domain resulting in a compact, low-power method of performing the signal computation. Due to inherent variation in fabrication processing, a large focal plane processor may have one or more pixels that provide erroneous signals, i.e., the pixel may always signal that it is being impinged with bright light when in fact this is not the case. These “bad pixels” may cause the analog computation to generate an incorrect result. Additionally, a given image may have an object in the field of view that interferes with the desired computation of some property of the desired object in the image.
As an example, image sensors are commonly used in a wide variety of image-tracking applications. One such application is that of a sun-based position sensor. In order to compute the sun's position using an imaging sensor, the sensor and associated computational circuitry must compute the centroid of the sun's image. Centroid computation is a very useful, well known quantity for image-tracking applications. Finding the centroid is an averaging process, the solution is robust to noise as well as insensitive to minor variations in illumination level. However, in practical applications, such as sun sensors, the illumination level of interfering objects that fall into the sensor's field of view (e.g., glint) may be significant enough so as to adversely affect the centroid computation, thereby causing an error in the reported sun position.
FIG. 1 is an illustration of a prior art focal plane processor 10 (integrated circuit) including an n×n array 12 of imaging pixels 13 and signal processing means, e.g., computational blocks 18, 19.
FIG. 2 is a more detailed illustration a representative imaging pixel 13 from among the plurality of imaging pixels which makes up the n×n pixel array 12. The imaging pixel 13 is shown to include transistors M1, M2 and M3, image element 22, row summing line ri, column summing line ci and reset line, reseti. Each pixel 13 contributes a current that is summed over the pixel's respective row and column.
Referring again to FIG. 1, the processor 10 generally operates as follows. For each column (co-cn−1) and row (r0-rn−1) of the n×n array 12, the imaging pixels are summed (each pixel contributes a current) after an integration period yielding n summed rows and n summed columns. Each summed row is passed to the row computational block 18 and each summed column is passed to the column computational block 19. The row and column computational blocks 18, 19 use the respective n summed row and n column currents to compute some desired property of the image, e.g., a centroid. As stated above, a drawback of this prior art configuration is that in the case where one or more non-uniformities (e.g., undesirable objects, bad pixels) exist in the image, there is no provision for their removal.
Thus, an improved processor would be desirable having a capability for removing the one or more non-uniformities thereby providing a more accurate computation of the desired property of the image.